This course is designed to impact the way you think about transforming data into better decisions. Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. The course on operations analytics, taught by three of Wharton’s leading experts, focuses on how the data can be used to profitably match supply with demand in various business settings. In this course, you will learn how to model future demand uncertainties, how to predict the outcomes of competing policy choices and how to choose the best course of action in the face of risk. The course will introduce frameworks and ideas that provide insights into a spectrum of real-world business challenges, will teach you methods and software available for tackling these challenges quantitatively as well as the issues involved in gathering the relevant data.
This course is appropriate for beginners and business professionals with no prior analytics experience.

JJ

Very useful and very informative. Loved the predictive and prescriptive part of this learning. Good knowledge to get into more advanced learning. Much much better than customer analytics course.

GC

Sep 16, 2018

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The topics is very much related to what I'm doing and I'm surprised that this course leads me to unchartered territory that brings me a lot of ways on how to solve day to day operations problem.

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Prescriptive Analytics, Low Uncertainty

In this module, you'll learn how to identify the best decisions in settings with low uncertainty by building optimization models and applying them to specific business challenges. During the week, you’ll use algebraic formulations to concisely express optimization problems, look at how algebraic models should be converted into a spreadsheet format, and learn how to use spreadsheet Solvers as tools for identifying the best course of action.

Sergei Savin

Noah Gans

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This video focuses on the set up for the solver on Google Sheets. You should watch this video after you watch the main video for session two. I have uploaded the spreadsheet for the Zooter problem to Google Sheets. This spreadsheet reflects the trail solution of 500 units of each Zooter time. I've also entered all the formulas for the objective function and for the use resource amounts. On Google Sheets the solver is one of the add-ons. In order to load the solver, we need to go to add-ons, click on get add-ons, type solver in the search box. And when you find it, install it. Okay, here we have solver appearing under add-ons. A couple of comments about the shortcuts. The shortcut for displaying and editing a formula in a particular cell in Google Sheets, is the same as in Windows F2. So, if we go to the objective function cell, F10, we can display and edit its content, using the same shortcut. The same applies to the shortcut F4 that can be used to impose absolute cell references. If we check the cell E14 and highlight the decision variable cells, We can change the addresses of the cells between absolute and relative by repeated pressing F4. Okay, let's scroll this over. Let's select add-ons, solver, start. This solver dialogue window appears on the right side of the sheet. Let's specify the objective function. In Google sheets it is convenient to first go to the objective function cell on the spreadsheet. And then go to the said objective. So now, we've selected the objective function. We do the same thing for decision variables. We highlight C10 and D10 first, and then go by changing box, and C10 and D10 appear there. Finally, constraints. We first click on add, then we highlight the cells E14, E16, then go to the left hand side. After that, we highlight G14, G16. And go to the right-hand side and then click okay. And now constrained has been added. Now, we need to specify that our decision variable's our integer. Again, we click add. We highlight C10 and D10, we go to left-hand side. And then in the relation box, we select integer and we click okay. And we see that our constraint is added. In solving method, we stay with the standard SLSGRG nonlinear, because it's pretty much the same as GRG nonlinear we used on Windows. Finally, we click on options and make sure that ignore integer is unchecked and assume non-negative is checked. The last option make sure that our decision variables are all non-negative. We click okay. And then we click solve. The solver starts working, and then displays the optimal solution.